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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Complex polycation redox material interfaced with renewable porous carbon for asymmetric supercapacitors

Mixed polycation transition metal ferrites are known to exhibit unique and superior characteristics for structural, electrical, magnetic, and optical applications. Although a few binary transition metal ferrites are found to be suitable for electrochemical energy storage application, ternary transition metal ferrites are not investigated for asymmetric supercapacitors (ASCs). Mixed polycation oxides are expected to have increased active sites that can facilitate proton and electron transfer impacting the redox reactions. Specific crystal structure and associated lattice parameters as well as surface and morphological characteristics can also influence the energy storage properties. This study for the first time reports a novel complex polycation redox material, (Cu p Mn q Zn r ) x Fe y O z and renewable pinewood (PW) derived porous carbon (POC) as electrodes for ASC. Both (Cu p Mn q Zn r ) x Fe y O z and PW-POC are subjected to electrochemical characterization and used in ASC configuration with aqueous KOH electrolyte. It is anticipated that the Faradaic characteristics of (Cu p Mn q Zn r ) x Fe y O z will make it to serve as a cathode while PW-POC with capacitive behavior will act as anode in ASCs. Relatively higher specific capacitance of > 200 F/g is observed for the (Cu p Mn q Zn r ) x Fe y O z reference electrode and fabricated ASCs. Capacitance retention rate is tested in 10,000 cycles for the working electrodes whereas for ASC, the stability tests are performed over 100 charging-discharging cycles exhibiting relatively higher capacitance retention. (Cu p Mn q Zn r ) x Fe y O z appears to be a promising material for a supercapacitor.

(CupMnqZnr)xFeyOz↗
DOE OSTI2024

Catalyzing deep decarbonization with federated battery diagnosis and prognosis for better data management in energy storage systems

Industrial data analytics methods play a central role in improving energy storage performance and efficiency, impacting the future of electrified transportation and renewable electricity generation. However, significant challenges hinder the large-scale deployment of batteries. Conventional methods rely on centralized collection and processing of fleet-level data, leading to database size issues and privacy concerns due to potential data breaches. To enable scalable deployment of battery management systems, this article proposes a federated battery diagnosis and prognosis model, which distributes the processing of battery standard current-voltage-time-usage data in a privacy-preserving manner. Instead of transferring the raw data, this approach communicates only the locally processed parameters, thus reducing communication load and preserving data confidentiality. The federated model offers a paradigm shift in battery health management through privacy-preserving distributed methods for battery data processing and lifetime prediction, ensuring the reliable and sustainable deployment of lithium-ion batteries in a rapidly evolving world.

asset health management↗
DOE OSTI2025

Ligand-Driven Electrochemical Tuning of Co 6 Se 8 Chevrel Clusters

Molecular “Chevrel-type” clusters of the formula Co 6 Se 8 L 6 (L = neutral ligand) are a well-studied class of clusters due to their utility as molecular analogues to the Chevrel extended solid phase and their application as subunits in hierarchical materials. However, their solution and optical properties remain relatively underexplored. Aiming to develop the fundamental relationships between the molecular and electronic structures of these clusters and their electrochemical and photophysical properties, this work reports the preparation of a series of Co 6 Se 8 (P­(C 6 H 4 R) 3 ) 6 -type clusters with R = Cl (1), F (2), H (3), CH 3 (4), and OCH 3 (5) via a stepwise synthetic approach. Solution and solid-state experimental characterization and density functional theory calculations reveal that the Co 6 Se 8 cores of 1–5 maintain consistent electronic and structural properties despite the variation of the triarylphosphine ligand para-substituent Hammett parameters (σ p ). However, cyclic voltammetry measurements indicate that the electron transfer energetics of 1–5 are strongly influenced by ligand substitution, with the E 1/2 of a given redox event spanning ∼0.5 V depending on the triarylphosphine ligand’s σ p . In conclusion, these findings support the characterization of Co 6 Se 8 clusters as atomically precise nanoclusters with both the structural robustness and the electrochemical tunability needed to act as components in larger charge transfer assemblies.

Wheaton, Amelia M. [Argonne National Laboratory (A↗
DOE OSTI2025

MHD Analysis of Dual-Coolant Lead-Lithium Blanket for Spherical Tokamak Advanced Reactor

The tritium breeding blanket is vital for future fusion power plants, with the Spherical Tokamak Advanced Reactor (STAR) project highlighting the dual-coolant lead-lithium (DCLL) design. The DCLL blanket performs shielding, energy exhaust, and tritium breeding using a lead-lithium alloy , with lithium as the breeder and lead as the neutron multiplier. It also serves as the primary coolant, with helium providing supplemental cooling. Reduced-activation ferritic/martensitic steel is used for the blanket structure. Magnetohydrodynamic (MHD) phenomena influence the liquid metal flow in a magnetic field, affecting heat transfer in the breeder affected by energetic neutrons. Understanding key flow parameters in such conditions is critical for efficient DCLL design. This study uses three-dimensional thermofluid MHD analysis with ANSYS CFX software, modified at Princeton Plasma Physics Laboratory, to simulate high Hartmann flows. The neutronics code MCNP, coupled with plasma equilibrium, provides heat source distribution. In conclusion, we examine electromagnetic interactions in adjacent fluid domains and analyze the magnetic field’s impact on flow distribution in the inboard and outboard blanket layout, using detailed mesh generation for accurate results.

DCLL↗
DOE OSTI2026

Angular momentum of vacuum bubbles in a first-order phase transition

The formation of primordial black holes (PBHs) during a first-order phase transition (FOPT) in a dark sector has been of recent interest. A quantity that characterizes a black hole is its spin. We carry out the first step towards determining the spin of such PBHs, by calculating the spin of spherical false vacuum bubbles induced by cosmological perturbations. The angular momentum is given by the product of density and velocity perturbations. We carefully track the evolution of background quantities and calculate the transfer functions during the FOPT. We find that the dimensionless spin parameter s = J /(G N M 2 ) of false vacuum bubbles of mass M and angular momentum J , take a wide range of values from 𝒪(10 -5 ) to 𝒪(10) for FOPTs between 10 keV and 100 GeV and a dark sector that is 0.1 to 0.4 times cooler than the visible sector. We also find a scaling relation between the root-mean-square value of the spin, the FOPT time scale, the bubble wall velocity, and the dark sector-to-visible sector temperature ratio.

cosmological phase transitions↗
DOE OSTI2025

XRISM spectroscopy on orbital modulation of Fe Ly α lines in Cygnus X-3

To understand physical processes such as mass transfer and binary evolution in X-ray binaries, the orbital parameters of the system are fundamental and crucial information. Cygnus X-3 is a high-mass X-ray binary composed of a compact object of unknown nature and a Wolf–Rayet star, which is of great interest in the context of wind-fed mass accretion and binary evolution. Here we present XRISM/Resolve high-resolution spectroscopy, focusing on the Fe Ly$\alpha$ lines when the source was in its hypersoft state. We perform an orbital phase-resolved spectral analysis of the lines to study the orbital modulation of the emission and absorption lines. It is found that the emission lines reflect the orbital motion of the compact object whose estimated velocity amplitude is $430^{+150}_{-140}$ km s$^{-1}$, while the absorption lines show a variation that can be interpreted as originating from the stellar wind. We discuss possible mass ranges for the binary components using the mass function with the estimated value of the velocity amplitude in this work, combined with the relation between the mass-loss rate and the orbital period derivative and the empirical mass and mass-loss rate relation for Galactic Wolf–Rayet stars. They are constrained to be (1.3–5.1) and (9.3–12) M$_\odot$, respectively, for the assumed inclination angle of $i =25^\circ$, and become more relaxed, (1.3–24) and (9.3–16) M$_\odot$, for $i = 35^\circ$. Thus, it remains unclear whether the system harbors a black hole or a neutron star.

X-rays: binaries↗
DOE OSTI2024

Sixteen multiple-amplifier sensing charge-coupled devices and characterization techniques targeting the next generation of astronomical instruments

We present a candidate sensor for future spectroscopic applications, such as a Stage-5 Spectroscopic Survey Experiment or the Habitable Worlds Observatory. This type of charge-coupled device (CCD) sensor features multiple in-line amplifiers at its output stage allowing multiple measurements of the same charge packet, either in each amplifier or in the different amplifiers. Recently, the operation of an eight-amplifier sensor has been experimentally demonstrated, and we present the operation of a 16-amplifier sensor. This new sensor enables a noise level of ∼1 erms− with a single sample per amplifier. In addition, it is shown that sub-electron noise can be achieved using multiple samples per amplifier. In addition to demonstrating the performance of the 16-amplifier sensor, we aim to create a framework for future analysis and performance optimization of this type of detectors. New models and techniques are presented to characterize specific parameters, which are absent in conventional CCDs and Skipper CCDs: charge transfer between amplifiers and independent and common noise in the amplifiers and their processing.

16 multiple-amplifer sensing CCD (MAS-CCD)↗
DOE OSTI2025

BEAST

The Bilinear Ensemble Actuation Synthesis Toolkit (BEAST) is a computational platform that optimizes time-varying control signals to achieve a specified transfer of states governed by bilinear ensemble systems in which model parameters are subject to uncertainty.

Zlotnik, anatoly↗
DOE OSTI2026

A Proof of the Asymptotic Variance of Path Length Estimators for Single-Collision Monte Carlo Source Iteration in the Thick Diffusion Limit

Here, we prove a theorem relating the variance of path length estimators for single-collision Monte Carlo source iteration to a parameter that becomes infinitesimally small in an important physical regime arising in radiative transfer. In our usage, “single-collision Monte Carlo source iteration” refers to Monte Carlo Boltzmann transport methods in which each Monte Carlo particle history includes no more than a single collision, and the physics of multiple scattering is modeled by lagging the scattering source term and iterating until this term converges. Our theorem can be used to construct variance reduction techniques which improve the order of the estimator variance. This enables calculations that would otherwise require impractically large sample sizes to achieve practical estimator uncertainties. We believe this is the first postulation of a theorem relating estimator variance to a limiting case parameter for single-collision Monte Carlo source iteration, and the first proof of such a theorem. We illustrate the theorem’s value with an example in which the authors of a transport method used the theorem to design a variance reduction technique that improved the uncertainty of their solution by a factor of about 500 for a proxy problem from radiative transfer that contains both optically-thick and optically-thin material.

Mathematics and Computing↗
DOE OSTI2024

Field Emission Current Transfer for Homopolar Machines

With the increasing electrification of transportation, the need for high power density electric machines is higher than ever. The required specific power for the more demanding applications, such as airplane propulsion, is over 20 kW/kg for multi-megawatt range power levels. Fully superconducting synchronous machines could reach the required performance, but significant challenges remain to be addressed such as AC losses management and rotating cryogenics implementation. Homopolar machines constitute the simplest electro-mechanical conversion systems possible, however the difficulty of establishing reliable and efficient low voltage, high DC current transfer from a stationary to a rotating system has prevented homopolar machines from competing with AC electrical machines. While sliding contacts or liquid metal contacts are feasible, they lead to high losses, high maintenance requirements and the use of environmentally unfriendly materials. We investigated field emission current transfer as an alternative to sliding contacts. We have demonstrated field emission current transfer in vacuum between a copper electrode and carbon nanotubes and diamond pyramids to evaluate the feasibility of contact-free current transfer for homopolar machines. The initial field emission testing was successfully demonstrated with current densities in the 10 mA/cm 2 range. The initial experiments validated the concept and supported the development of a roadmap for the development of contactless current transfer for homopolar machines, helped understand the limitations of the current test system and identify the key parameters that will lead to better performance.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

RSPECT: A PROSPECT-based model incorporating the real structure of rice leaves

Radiative transfer models (RTMs) describe how light is absorbed, scattered, and transmitted within leaves by simulating mechanistic light propagation processes. The PROSPECT model is based on measurable parameters (the leaf biochemical content) and a non-measurable parameter (the leaf anatomical structure represented by the leaf structure parameter (N)). The effect of N on the optical properties of leaves has been investigated through a number of local and global sensitivity analyses. Other studies have directly evaluated the effect of the leaf anatomical structure on spectral reflectance, particularly in the near infrared region. However, the relationship between N and the anatomical structure is unclear. Here, in this study, we leveraged eLeaf, a ray tracing-based 3D rice leaf simulator, to establish relationships between leaf anatomical features and spectral properties, enabling us to replace N in the PROSPECT-4 model with measurable leaf anatomical parameters and develop the RSPECT model. The leaf thickness at minor vein, leaf thickness at bulliform cells, mesophyll thickness at minor vein, and distance between two minor veins could be used to predict N effectively. The RSPECT model achieved spectral simulation accuracy comparable to PROSPECT-4 and was more suitable for parameter inversion of the physical and chemical properties of rice leaves, with relative root mean square errors of 7.4% for chlorophyll content, 5.6% for equivalent water thickness, and 7.5% for dry matter content. In conclusion, RSPECT improves radiative transfer modeling by integrating measurable anatomical features and provides a framework for extending this approach to other vegetation types.

hyperspectral↗
DOE OSTI2025

Pump with Broadband Probe Experiments for Single-Shot Measurements of Plasma Conditions and Crossed-Beam Energy Transfer

Here, a novel technique for measuring plasma conditions using monochromatic pump-broadband-probe laser interactions has been experimentally demonstrated. Originally proposed in Ludwig et al. [Phys. Plasmas 26, 113108 (2019)], this method utilizes crossed-beam energy transfer between the broadband probe and the pump, mediated by plasma ion acoustic waves. The complete energy transfer spectrum can be captured in a single shot, enabling the inference of plasma parameters such as density, electron and ion temperatures, and flow velocity. Compared to Thomson scattering, this technique offers signal enhancements typically larger than 9 orders of magnitude, significantly reducing the required probe laser intensity and facilitating interactions that are linear and measurements that are nonperturbative of the plasma. Furthermore, it provides a powerful tool for advancing studies of crossed-beam energy transfer under conditions relevant to inertial confinement fusion experiments.

Physics - Plasma physics↗
DOE OSTI2026

Validated Reactive Force Field Quantifies MXene Interfacial Properties, Mechanics, and Thermal Transport

MXenes combine rich surface chemistry, mechanical strength, and high conductivity for a multitude of emerging applications. Predictive modeling supports accelerated materials designs and has been limited by the absence of validated and transferable force fields. Here, we introduce an interpretable, reactive INTERFACE force field (IFF and IFF-R) for Ti 3 C 2 T x MXenes that is trained based on chemical knowledge and achieves quantitative agreement with experiments across lattice parameters (<0.5%), density (<0.2%), liquid contact angles, Raman spectra, and the in-plane elastic modulus (∼320 GPa). The models cover surface terminations from hydroxyl (−OH) to fluorine (−F) groups and are extensible to other chemistries. We introduce pH-resolved surface chemistry and identify dopamine adsorption mechanisms at MXene–aqueous interfaces supported by QCM-D and UV–Vis experiments. The data reveal coplanar and perpendicular binding modes and concentration-dependent multilayer assembly. We predict previously inaccessible properties, including termination-dependent cleavage energies, interlayer shear moduli and dynamic shear failure, nanoindentation and brittle fracture, anisotropic in-plane and out-of-plane thermal conductivities, including the role of defects. Agreement with available experimental data is consistently close and exceeds DFT accuracy across the benchmark properties examined. The IFF/IFF-R model is compatible with CHARMM, AMBER, OPLS, and CVFF force fields for simulations of MXenes with diverse surface terminations, electrolyte interfaces, biointerfaces, and polymer composites without additional parameters. Parameter sets, 3D models, and analysis scripts are provided for community use. The validated, reactive, and transferable IFF framework facilitates predictive design of MXene-based films, membranes, sensing interfaces, and composites.

MXene↗
DOE OSTI2024

Model-Based Energy and Cost Analysis of Direct Air Capture Using ePTFE-Based Laminate-Structured Gas–Solid Contactors

Carbon dioxide removal (CDR) technologies will play a significant role in limiting global warming if implemented on a large scale. Direct air capture (DAC) is a scalable approach for removing atmospheric carbon, yet the true scope of its scalability remains unclear due to the early stage of technology development and high first plant costs. This study provides groundwork for understanding the technoeconomic trade-offs in developing DAC systems using laminate-structured gas–solid contactors, encompassing the analysis of both contactor and process design spaces. The robust mass transfer and process models outlined in this study provide tools for evaluating DAC processes and designing DAC plants based on cost and energy analysis. First, the key contactor geometrical parameters are identified to understand the CO 2 productivity–energy demand trade-offs, where geometries yielding higher mass transfer rates can achieve higher CO 2 productivities at the expense of energy consumption by fans and steam use. Next, a detailed process parametric study is conducted for DAC systems coupled with steam-assisted temperature-vacuum swing adsorption (S-TVSA) to visualize the trade-offs in the multidimensional design space. The main cost driver dramatically changes over different process conditions, but the operating cost prevailed on the Pareto front, with potential to operate as low as 150 $/tonne-CO 2 (within the cost range of 148–504 $/tonne-CO 2 in this study where the DAC system is coupled with industrial facilities for steam production).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Compressing Vision Transformers in Geospatial Transfer Learning with Manifold-Constrained Optimization

Deploying geospatial foundation models on resource-constrained edge devices demands compact architectures that maintain high downstream performance. However, their large parameter counts and the accuracy loss often induced by compression limit practical adoption.In this work, we leverage manifold-constrained optimization framework DLRT to compress large vision transformer–based geospatial foundation models during transfer learning. By enforcing structured low-dimensional parameterizations aligned with downstream objectives, this approach achieves strong compression while preserving task-specific accuracy. We show that the method outperforms of-the-shelf low-rank methods as LoRA. Experiments on diverse geospatial benchmarks confirm substantial parameter reduction with minimal accuracy loss, enabling high-performing, on-device geospatial models.

Snyder, Thomas [Yale University]↗
DOE OSTI2025

Revealing the Influence of Binding Motifs on Electron Transfer and Recombination Kinetics for CdSe Quantum Dots Functionalized with a Modified Viologen

Anchoring of molecules to the surfaces of semiconductor nanocrystals (NCs) presents an opportunity to leverage the precise synthetic tunability of molecular function and the remarkable light harvesting properties of NCs to drive photochemical reactions. However, charge transfer between the two species depends not only on the energy level alignments but also on the details of their binding interactions, which are difficult to probe. Here, in this work, we characterize the binding between CdSe quantum dots (QDs) and a new phosphonated derivative of the electron acceptor methyl viologen, designed to attach to the QD surface via the phosphonate group. We use isothermal titration calorimetry to probe the thermodynamics of the QD–molecule interaction and use the parameters determined therein to analyze transient absorption spectroscopy measurements of forward and back electron transfer from QDs to the viologen. We find that the ligand-like phosphonate binding leads to an electron-transfer rate constant that is 3 orders of magnitude smaller than that for the face-on binding of the bipyridine ring of methyl viologen. Back electron transfer is also significantly slower in the derivative. Interestingly, a minor fraction of the phosphonated derivative also binds in the face-on configuration, with similar forward and back electron transfer kinetics as methyl viologen. Numerical simulations show that the ligand-like binding will lead to significantly improved quantum yields of photocatalysis over a wide range of reaction rates. By independently characterizing binding thermodynamics and charge transfer kinetics, this work reveals how the complexities underlying electron transfer at the NC–molecule interface determine photocatalytic outcomes. This work also represents a step toward controlling forward and back electron transfer kinetics via rational molecular design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Non-dimensional performance and safety parameters for heat pipes

The use of heat pipes in safety-critical systems such as nuclear microreactors dictates the development of generalized, practical, scalable performance and safety parameters. Traditional dimensional metrics, while informative, lack the universality required for comparative analysis across varying designs and operating regimes. Here, this work introduces a comprehensive set of non-dimensional parameters to characterize heat pipe performance and safety, including capillary performance, effective thermal conductivity, response time, exergetic efficiency, allowable temperature gradients, allowable rate of temperature change, priming coefficients, and factor of safety. A reference heat pipe design representative of microreactor applications was analyzed via the developed parameters using both traditional analytical models and Sockeye simulations under transient and steady-state conditions. Sodium, potassium, and water were evaluated as working fluids to demonstrate the applicability of the framework across a broad temperature range. The proposed non-dimensional parameters effectively captured key thermal-hydraulic behaviors and safety concerns, as was demonstrated via Sockeye simulations. This framework supports the development of design optimization strategies, operational protocols, and safety assurance practices for advanced reactor systems and other high-reliability applications.

42 - ENGINEERING↗
DOE OSTI2026

What do physics-informed DeepONets learn? Understanding and improving training for scientific computing applications

Physics-informed deep operator networks (DeepONets) have emerged as a promising approach toward numerically approximating the solution of partial differential equations (PDEs). In this work, we aim to develop further understanding of what is being learned by physics-informed DeepONets by assessing the universality of the extracted basis functions and demonstrating their potential toward model reduction with spectral methods. Results provide clarity about measuring the performance of a physics-informed DeepONet through the decays of singular values and expansion coefficients. In addition, we propose a transfer learning approach for improving training for physics-informed DeepONets between parameters of the same PDE as well as across different, but related, PDEs where these models struggle to train well. This approach results in significant error reduction and learned basis functions that are more effective in representing the solution of a PDE.

Deep operator networks↗